航空学报 > 2015, Vol. 36 Issue (4): 1212-1220   doi: 10.7527/S1000-6893.2014.0275

基于区实混合序列相似度的异步不等速率航迹关联算法

衣晓, 韩健越, 张怀巍, 关欣   

  1. 海军航空工程学院 电子信息工程系, 烟台 264001
  • 收稿日期:2014-05-21 修回日期:2014-10-08 出版日期:2015-04-15 发布日期:2014-10-14
  • 通讯作者: 衣晓Tel.: 0535-6635673 E-mail: yxgx_gxyx@163.com E-mail:yxgx_gxyx@163.com
  • 作者简介:衣晓 男, 博士, 教授。主要研究方向: 多传感器信息融合, 导航新技术, 无线传感器网络, 智能计算。Tel: 0535-6635673 E-mail: yxgx_gxyx@163.com
  • 基金资助:

    国家自然科学基金(61032001); 教育部新世纪优秀人才支持计划(NCET-11-0872)

Asynchronous track-to-track association algorithm based on similarity degree of interval-real sequence

YI Xiao, HAN Jianyue, ZHANG Huaiwei, GUAN Xin   

  1. Department of Electronic and Information Engineering, Naval Aeronautical Engineering Institute, Yantai 264001, China
  • Received:2014-05-21 Revised:2014-10-08 Online:2015-04-15 Published:2014-10-14
  • Supported by:

    National Natural Science Foundation of China(61032001); Program for New Century Excellent Talents in University of Ministry of Education of China(NCET-11-0872)

摘要:

在分布式多目标跟踪系统中,由于局部传感器开机时间、采样频率以及通信延迟不同等原因,导致来自各传感器的局部航迹往往是异步不等速率的。目前一般的方法是先进行时域配准再进行航迹关联,但是在同步化的过程中,航迹估计值的误差会发生传播,影响航迹关联的性能。针对此问题,提出了一种基于区实混合序列相似度的异步不等速率航迹关联算法。算法首先通过区间数-实数混合序列变换(IRST)得到等长度的航迹行为序列,然后定义一种新的序列差异信息度量,得到混合序列的相似度,以此进行航迹关联判定。仿真实验表明,该算法可以有效地解决异步不等速率航迹关联问题,并且通信延迟和数据乱序对算法性能的影响不明显。

关键词: 异步航迹, 区间灰数, 航迹关联, 目标跟踪, 信息融合

Abstract:

Because local sensors in the distributed multi-target tracking system usually start working at different time and provide tracks at different rates with different communication delays, the local tracks from different sensors are usually asynchronous. The current solution is to synchronize the tracks before track association. But the estimation error spreads when synchronizing, which affects the performance of correlation. To solve the problem, an asynchronous track-to-track association method based on similarity degree of interval-real sequence is presented. Firstly, the track sequences are transformed to same-length sequences which contain interval data and real data by interval-real sequence transform (IRST). Then a new difference measurement for the sequences is defined, by which the correlation degree can be calculated and the track association conclusion be made. Simulation results show that the presented method can effectively solve the asynchronous track-to-track association problem, and its performance is seldom affected in the case of different communication delays and disorderly data.

Key words: asynchronous track, interval grey number, track association, target tracking, information fusion

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